Staff Machine Learning Engineer (L4) · Twilio

Sat, 25 Apr 2026 21:01:30 GMT
Engineering

Twilio · Remote - India · remote

Join the team as Twilio's next Staff Machine Learning Engineer.

This position is needed to scope, design, and deploy machine learning systems into the real world. The individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio's AI/ML products and services.

You will understand customers' needs, build data products that work at a global scale, and own end-to-end execution of large-scale ML solutions.

To thrive in this role, you must have a deep background in ML engineering and a consistent track record of solving data & machine-learning problems at scale.

Responsibilities:

Build and maintain scalable machine learning solutions in production

Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness

Demonstrate end-to-end understanding of applications and develop a deep understanding of the 'why' behind our models & systems

Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements, and define the scope of the systems needed

Work closely with data platform teams to build robust scalable batch and real-time data pipelines

Collaborate with software engineers to build tools to enhance productivity and to ship and maintain ML models

Drive high engineering standards on the team through mentoring and knowledge sharing

Uphold engineering best practices around code reviews, automated testing, and monitoring

Qualifications:

7+ years of applied ML experience with proficiency in Python

Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning

Track record of building, shipping, and maintaining Machine Learning models in production in an ambiguous and fast-paced environment

Track record of designing and architecting large-scale experiments and analysis to inform product roadmap

Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring

Demonstrated ability to ramp up, understand, and operate effectively in new application/business domains

Experience working in an agile team environment with changing priorities

Experience of working on AWS

Desired:

Experience with Large Language Models

Travel:

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.